A Novel Optimal Deployment Algorithm for Fog Computing Nodes in Intelligent Logistics System with Efficient Energy Management and Load Balancing

Intelligent logistics system in Industry 4.0 involves the emergence of fog computing in handling various IoT sensors attached for automating the logistics system. Instead of transmitting massive data from the sensors to the cloud center, it will be processed by the fog nodes which provide faster response thereby avoiding heavy traffic and delay. While determining the location of fog nodes in building the logistics system, energy consumption and load balancing became major challenges. This work proposes a novel method to determine the location of fog nodes, edge devices and gateways under the minimal energy consumption of the fog nodes and optimal load balancing. In this work, artificial bee colony is combined with genetic algorithm to find the best location for the placement of edge devices, fog nodes and gateways with the objective of minimal deployment cost. Finally, the results show that the proposed method causes 11.9 % reduction in the deployment cost compared to other existing methods, however also ensure minimal energy consumption and optimal load balancing among the fog computing nodes used in this system.